1. Field of the Invention
The subject disclosure relates to methods and systems for scheduling and rescheduling resources used to accomplish activities, and more particularly to an improved method and system for scheduling and rescheduling fleet vehicles before, during and after a disruption in operation.
2. Background of the Related Art
Businesses in many areas utilize resources in complicated schedules to accomplish activities. For example, airlines, railways, buses, production lines and hospitals all have various resources including vehicles, machinery, floor space and personnel that must be coordinated on a grand scale. However, the schedules are subject to change based upon circumstances beyond the businesses control, profit objectives, policy changes and otherwise. When such disruptions occur, operations managers are typically unable to quickly and efficiently reschedule continuing operations without aid. In view of the above, several systems have been developed to aid decision making by proposing options for reallocating resources to achieve completion of the necessary activities. Such aids have been widely used and well understood in areas as diverse as airlines, railways, supply chains and logistics. Some examples are illustrated in U.S. Pat. No. 6,314,361, European Patent App. No. 1,195,670 and PCT Patent App. No. WO 02/097570 which are incorporated herein by reference.
There are problems associated with the systems and methods of the prior art. Many algorithms are well know that apply operations to produce every combination in the neighborhood and pick the cheapest solution. However, this brute force approach may take unduly long as the size of the neighborhood may require execution of a large number of operations and a small “optimality gap” is acceptable to expedite selecting a solution. The “optimality gap” is the difference between a low cost solution that may be found quickly and an optimal solution that may take tremendous effort to find. Typically, prior art systems are designed to find a solution for a very large scale problem resulting from a major disruption. Moreover, such systems and methodology often take unacceptably long intervals to develop solutions which remain suboptimal. Although a plurality of solutions may be offered to the operations manager, the plurality tend to be minor variations upon the same solution rather than significantly different alternatives. There is a need, therefore, for an improved system and method which approaches optimally solving disruptions with a focus on the typical day to day minor disruptions and, yet is scalable to assist in very larger scale disruptions. Such an improved system would offer a plurality of structurally different solutions.
Additionally, operations may involve multiple coordinated resources. For example, in the airline industry, operations managers often have to reschedule aircraft fleets as well as significant rescheduling of airline crews and passengers. Heretofore, an optimization aid used for one resource has been unable to interact with other optimization aids for the related resources. As a result, significant resources and valuable time are consumed pursuing rescheduling that is acceptable for utilizing one resource but completely unacceptable when the total impact is considered.
For example, U.S. Pat. No. 6,314,361 to Yu et al. shows an optimization server that processes a request from a user for optimal solutions to a specific flight schedule disruption. In response to the request, the optimization server initiates an aircraft optimization engine. The aircraft optimization engine processes the request and generates a set of solutions to overcome the disruption. In turn, the aircraft optimization engine initializes a crew optimization engine to determine whether the set of flight solutions are efficiently supported by flight and service crews. Many of the solutions or options produced by the aircraft optimization engine, although reasonably optimized in consideration of aircraft utilization, turn out to be wholly unacceptable options when viewed in light of the ramifications upon crew and passenger inconvenience. Thus, critical resources and time are utilized to produce and evaluate solutions which are unacceptable and must be discarded. Accordingly, what is also needed is an integrated operations framework which allows information to be exchanged among different resource optimization engines prior to generating solutions to yield an overall optimum solution without expending critical resources on solutions directed to a portion of the solution without considering the whole.